Comparative proteomics of liver and plasma on the CDAA rat NASH model

Nonalcoholic steatohepatitis (NASH) is a major cause of liver fibrosis with increasing prevalence worldwide. Currently there are no approved drugs available. The development of new therapies is difficult as diagnosis and staging requires biopsies. Consequently, predictive plasma biomarkers would be useful for drug development. To identify new plasma biomarkers in a choline-deficient L-amino acid-defined diet rat NASH model we analyzed liver and plasma samples by proteomics, revealing disease relevant signatures and a high correlation between liver mRNA and protein changes. We developed a multi-dimensional attribute ranking approach integrating multi-omics data with liver histology and prior knowledge uncovering known human markers, but also novel candidates. Using regression analysis, we show that the top-ranked plasma markers were highly predictive for fibrosis in our model and hence can serve as preclinical plasma biomarkers. Our approach presented here illustrates the power of multi-omics analyses combined with plasma proteomics and is readily applicable to human biomarker discovery.